// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2014 Navdeep Jaitly <ndjaitly@google.com and
//                    Benoit Steiner <benoit.steiner.goog@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

#include "main.h"

#include <Eigen/CXX11/Tensor>

using Eigen::array;
using Eigen::Tensor;

template<int DataLayout>
static void
test_simple_reverse()
{
	Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7);
	tensor.setRandom();

	array<bool, 4> dim_rev;
	dim_rev[0] = false;
	dim_rev[1] = true;
	dim_rev[2] = true;
	dim_rev[3] = false;

	Tensor<float, 4, DataLayout> reversed_tensor;
	reversed_tensor = tensor.reverse(dim_rev);

	VERIFY_IS_EQUAL(reversed_tensor.dimension(0), 2);
	VERIFY_IS_EQUAL(reversed_tensor.dimension(1), 3);
	VERIFY_IS_EQUAL(reversed_tensor.dimension(2), 5);
	VERIFY_IS_EQUAL(reversed_tensor.dimension(3), 7);

	for (int i = 0; i < 2; ++i) {
		for (int j = 0; j < 3; ++j) {
			for (int k = 0; k < 5; ++k) {
				for (int l = 0; l < 7; ++l) {
					VERIFY_IS_EQUAL(tensor(i, j, k, l), reversed_tensor(i, 2 - j, 4 - k, l));
				}
			}
		}
	}

	dim_rev[0] = true;
	dim_rev[1] = false;
	dim_rev[2] = false;
	dim_rev[3] = false;

	reversed_tensor = tensor.reverse(dim_rev);

	VERIFY_IS_EQUAL(reversed_tensor.dimension(0), 2);
	VERIFY_IS_EQUAL(reversed_tensor.dimension(1), 3);
	VERIFY_IS_EQUAL(reversed_tensor.dimension(2), 5);
	VERIFY_IS_EQUAL(reversed_tensor.dimension(3), 7);

	for (int i = 0; i < 2; ++i) {
		for (int j = 0; j < 3; ++j) {
			for (int k = 0; k < 5; ++k) {
				for (int l = 0; l < 7; ++l) {
					VERIFY_IS_EQUAL(tensor(i, j, k, l), reversed_tensor(1 - i, j, k, l));
				}
			}
		}
	}

	dim_rev[0] = true;
	dim_rev[1] = false;
	dim_rev[2] = false;
	dim_rev[3] = true;

	reversed_tensor = tensor.reverse(dim_rev);

	VERIFY_IS_EQUAL(reversed_tensor.dimension(0), 2);
	VERIFY_IS_EQUAL(reversed_tensor.dimension(1), 3);
	VERIFY_IS_EQUAL(reversed_tensor.dimension(2), 5);
	VERIFY_IS_EQUAL(reversed_tensor.dimension(3), 7);

	for (int i = 0; i < 2; ++i) {
		for (int j = 0; j < 3; ++j) {
			for (int k = 0; k < 5; ++k) {
				for (int l = 0; l < 7; ++l) {
					VERIFY_IS_EQUAL(tensor(i, j, k, l), reversed_tensor(1 - i, j, k, 6 - l));
				}
			}
		}
	}
}

template<int DataLayout>
static void
test_expr_reverse(bool LValue)
{
	Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7);
	tensor.setRandom();

	array<bool, 4> dim_rev;
	dim_rev[0] = false;
	dim_rev[1] = true;
	dim_rev[2] = false;
	dim_rev[3] = true;

	Tensor<float, 4, DataLayout> expected(2, 3, 5, 7);
	if (LValue) {
		expected.reverse(dim_rev) = tensor;
	} else {
		expected = tensor.reverse(dim_rev);
	}

	Tensor<float, 4, DataLayout> result(2, 3, 5, 7);

	array<ptrdiff_t, 4> src_slice_dim;
	src_slice_dim[0] = 2;
	src_slice_dim[1] = 3;
	src_slice_dim[2] = 1;
	src_slice_dim[3] = 7;
	array<ptrdiff_t, 4> src_slice_start;
	src_slice_start[0] = 0;
	src_slice_start[1] = 0;
	src_slice_start[2] = 0;
	src_slice_start[3] = 0;
	array<ptrdiff_t, 4> dst_slice_dim = src_slice_dim;
	array<ptrdiff_t, 4> dst_slice_start = src_slice_start;

	for (int i = 0; i < 5; ++i) {
		if (LValue) {
			result.slice(dst_slice_start, dst_slice_dim).reverse(dim_rev) =
				tensor.slice(src_slice_start, src_slice_dim);
		} else {
			result.slice(dst_slice_start, dst_slice_dim) =
				tensor.slice(src_slice_start, src_slice_dim).reverse(dim_rev);
		}
		src_slice_start[2] += 1;
		dst_slice_start[2] += 1;
	}

	VERIFY_IS_EQUAL(result.dimension(0), 2);
	VERIFY_IS_EQUAL(result.dimension(1), 3);
	VERIFY_IS_EQUAL(result.dimension(2), 5);
	VERIFY_IS_EQUAL(result.dimension(3), 7);

	for (int i = 0; i < expected.dimension(0); ++i) {
		for (int j = 0; j < expected.dimension(1); ++j) {
			for (int k = 0; k < expected.dimension(2); ++k) {
				for (int l = 0; l < expected.dimension(3); ++l) {
					VERIFY_IS_EQUAL(result(i, j, k, l), expected(i, j, k, l));
				}
			}
		}
	}

	dst_slice_start[2] = 0;
	result.setRandom();
	for (int i = 0; i < 5; ++i) {
		if (LValue) {
			result.slice(dst_slice_start, dst_slice_dim).reverse(dim_rev) =
				tensor.slice(dst_slice_start, dst_slice_dim);
		} else {
			result.slice(dst_slice_start, dst_slice_dim) =
				tensor.reverse(dim_rev).slice(dst_slice_start, dst_slice_dim);
		}
		dst_slice_start[2] += 1;
	}

	for (int i = 0; i < expected.dimension(0); ++i) {
		for (int j = 0; j < expected.dimension(1); ++j) {
			for (int k = 0; k < expected.dimension(2); ++k) {
				for (int l = 0; l < expected.dimension(3); ++l) {
					VERIFY_IS_EQUAL(result(i, j, k, l), expected(i, j, k, l));
				}
			}
		}
	}
}

EIGEN_DECLARE_TEST(cxx11_tensor_reverse)
{
	CALL_SUBTEST(test_simple_reverse<ColMajor>());
	CALL_SUBTEST(test_simple_reverse<RowMajor>());
	CALL_SUBTEST(test_expr_reverse<ColMajor>(true));
	CALL_SUBTEST(test_expr_reverse<RowMajor>(true));
	CALL_SUBTEST(test_expr_reverse<ColMajor>(false));
	CALL_SUBTEST(test_expr_reverse<RowMajor>(false));
}
